What is alpha commonly set at?

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Multiple Choice

What is alpha commonly set at?

Explanation:
Alpha is the threshold used to decide when a result is statistically significant. It represents the probability of rejecting the null hypothesis when it is actually true—a false positive. Setting alpha at 0.05 means you’re willing to accept a 5% risk of a Type I error and you require p-values below 0.05 to call something significant. This 5% standard provides a conventional balance between detecting real effects and avoiding false alarms, and it ties to a 95% confidence level for confidence intervals. Using a much smaller alpha (like 0.01) makes the test more stringent, reducing false positives but increasing the chance of missing real effects. A larger alpha (such as 0.10 or 0.50) would make it too easy to claim significance, inflating false positives.

Alpha is the threshold used to decide when a result is statistically significant. It represents the probability of rejecting the null hypothesis when it is actually true—a false positive. Setting alpha at 0.05 means you’re willing to accept a 5% risk of a Type I error and you require p-values below 0.05 to call something significant. This 5% standard provides a conventional balance between detecting real effects and avoiding false alarms, and it ties to a 95% confidence level for confidence intervals. Using a much smaller alpha (like 0.01) makes the test more stringent, reducing false positives but increasing the chance of missing real effects. A larger alpha (such as 0.10 or 0.50) would make it too easy to claim significance, inflating false positives.

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